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cs.DS updates on arXiv.org

PAC Learning with Bandit Feedback: Sharp Sample Complexity in the Realizable Setting Algorithms with Polynomially-Improved Approximation Factors for the $2 \rightarrow q$ Norm, and Applications A computational phase transition for learning-to-sample from Ising models Covering vertices by sequential stars Fermi-Dirac machines as quantizations of neurons A Comprehensive Evaluation of Vertex Elimination Algorithms for Algorithmic Differentiation A Tight Bound on Localization of Electrical Flows Optimal Dimension-Free Sampling for Regularized Classification Reducing the Randomness in Partition Oracles for Bounded Degree Minor-Free Graphs Beyond the Half-Approximation: Fair and Efficient Online Class Matching Efficient Uniform Sampling of Surjections via their Profiles Tractable Maximization of Budgeted Phylogenetic Diversity on Networks Utilizing Node Scanwidth Fairness in Aggregation: Optimal Top-$k$ and Improved Full Ranking Learning-Augmented Online Scheduling with Parsimonious Preemption Entropy Equivalence Testing Lumberjack: Better Differentially Private Random Forests through Heavy Hitter Detection in Trees The Secretary Problem with a Stochastic Precursor Polynomial-Time Robust Multiclass Linear Classification under Gaussian Marginals Efficient Banzhaf-Based Data Valuation for $k$-Nearest Neighbors Classification Block-Sphere Vector Quantization An Approximation Algorithm for Graph Label Selection Iterative Chow Filtering for Learning with Distribution Shift Complexity of Non-Log-Concave Sampling in Fisher Information Stochastic Matching via Local Sparsification Finite Sample Bounds for Learning with Score Matching What is Learnable in Valiant's Theory of the Learnable? Provable Quantization with Randomized Hadamard Transform Min-Max Optimization Requires Exponentially Many Queries Fast and Compact Graph Cuts for the Boykov-Kolmogorov Algorithm A proximal gradient algorithm for composite log-concave sampling
Faster Minimum k-cut of a Simple Graph
Jason Li · 2019-10-07 · via cs.DS updates on arXiv.org

We consider the (exact, minimum) $k$-cut problem: given a graph and an integer $k$, delete a minimum-weight set of edges so that the remaining graph has at least $k$ connected components. This problem is a natural generalization of the global minimum cut problem, where the goal is to break the graph into $k=2$ pieces. Our main result is a (combinatorial) $k$-cut algorithm on simple graphs that runs in $n^{(1+o(1))k}$ time for any constant $k$, improving upon the previously best $n^{(2ω/3+o(1))k}$ time algorithm of Gupta et al.~[FOCS'18] and the previously best $n^{(1.981+o(1))k}$ time combinatorial algorithm of Gupta et al.~[STOC'19]. For combinatorial algorithms, this algorithm is optimal up to $o(1)$ factors assuming recent hardness conjectures: we show by a straightforward reduction that $k$-cut on even a simple graph is as hard as $(k-1)$-clique, establishing a lower bound of $n^{(1-o(1))k}$ for $k$-cut. This settles, up to lower-order factors, the complexity of $k$-cut on a simple graph for combinatorial algorithms.